| Understanding autoencoders with information theoretic concepts S Yu, JC Principe Neural Networks 117, 104-123, 2019 | 138 | 2019 |
| Understanding Convolutional Neural Networks with Information Theory: An Initial Exploration S Yu, K Wickstrøm, R Jenssen, JC Principe IEEE Transactions on Neural Networks and Learning Systems, 2020 | 95* | 2020 |
| Multi-view manifold learning with locality alignment Y Zhao, X You, S Yu, C Xu, W Yuan, XY Jing, T Zhang, D Tao Pattern Recognition 78, 154-166, 2018 | 82 | 2018 |
| Multivariate Extension of Matrix-based Renyi's α-order Entropy Functional S Yu, LGS Giraldo, R Jenssen, JC Principe IEEE Transactions on Pattern Analysis and Machine Intelligence, 2019 | 81 | 2019 |
| Concept drift detection with hierarchical hypothesis testing S Yu, Z Abraham Proceedings of the 2017 SIAM International Conference on Data Mining, 768-776, 2017 | 61 | 2017 |
| Multi-view non-negative matrix factorization by patch alignment framework with view consistency W Ou, S Yu, G Li, J Lu, K Zhang, G Xie Neurocomputing 204, 116-124, 2016 | 59 | 2016 |
| Concept drift detection and adaptation with hierarchical hypothesis testing S Yu, Z Abraham, H Wang, M Shah, Y Wei, JC Príncipe Journal of the Franklin Institute 356 (5), 3187-3215, 2019 | 53 | 2019 |
| Improved functional link artificial neural network via convex combination for nonlinear active noise control H Zhao, X Zeng, Z He, S Yu, B Chen Applied Soft Computing 42, 351-359, 2016 | 51 | 2016 |
| Kernel learning for dynamic texture synthesis X You, W Guo, S Yu, K Li, JC Príncipe, D Tao IEEE Transactions on Image Processing 25 (10), 4782-4795, 2016 | 39 | 2016 |
| Request-and-Reverify: Hierarchical Hypothesis Testing for Concept Drift Detection with Expensive Labels S Yu, X Wang, JC Principe Proceedings of the 27th International Joint Conference on Artificial …, 2018 | 36 | 2018 |
| Information Plane Analysis of Deep Neural Networks via Matrix-Based Renyi's Entropy and Tensor Kernels K Wickstrøm, S Løkse, M Kampffmeyer, S Yu, J Principe, R Jenssen arXiv preprint arXiv:1909.11396, 2019 | 32 | 2019 |
| Co-regularized multiview nonnegative matrix factorization with correlation constraint for representation learning W Ou, F Long, Y Tan, S Yu, P Wang Multimedia Tools and Applications 77 (10), 12955-12978, 2018 | 28 | 2018 |
| STFT-like time frequency representations of nonstationary signal with arbitrary sampling schemes S Yu, X You, W Ou, X Jiang, K Zhao, Z Zhu, Y Mou, X Zhao Neurocomputing 204, 211-221, 2016 | 27 | 2016 |
| A new algorithm for shoreline extraction from satellite imagery with non-separable wavelet and level set method S Yu, Y Mou, D Xu, X You, L Zhou, W Zeng International Journal of Machine Learning and Computing 3 (1), 158, 2013 | 27 | 2013 |
| Deep Deterministic Information Bottleneck with Matrix-Based Entropy Functional X Yu, S Yu, JC Príncipe ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021 | 23 | 2021 |
| Modularizing deep learning via pairwise learning with kernels S Duan, S Yu, JC Príncipe IEEE Transactions on Neural Networks and Learning Systems, 2021 | 22 | 2021 |
| Dynamic texture modeling and synthesis using multi-kernel Gaussian process dynamic model Z Zhu, X You, S Yu, J Zou, H Zhao Signal Processing 124, 63-71, 2016 | 20 | 2016 |
| Measuring Dependence with Matrix-based Entropy Functional S Yu, F Alesiani, X Yu, R Jenssen, JC Principe Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI-21), 2021 | 19 | 2021 |
| Content-adaptive rain and snow removal algorithms for single image S Yu, Y Zhao, Y Mou, J Wu, L Han, X Yang, B Zhao Advances in Neural Networks–ISNN 2014: 11th International Symposium on …, 2014 | 18 | 2014 |
| On kernel method–based connectionist models and supervised deep learning without backpropagation S Duan, S Yu, Y Chen, JC Principe Neural computation 32 (1), 97-135, 2020 | 16 | 2020 |
jose principeprofessor of ECE, U. of FloridaVerified email at cnel.ufl.edu
